This project is concerned with the factors that determine one aspect of human exposure potentials on contaminated sites. The focus is on vapor inhalation potential. The project involves a combined experimental and modeling study, and has a particular emphasis on mixtures and how these influence the exposure processes. The modeling portion of the study involves further development and validation of a threedimensional computational fluid dynamics model that includes the many variables that can play a role in determining exposures. Earlier models of vapor intrusion have often involved simple one-dimensional descriptions of the phenomenon, and are not adequate for describing the actual situation in the field. Likewise, we are interested in examining transient effects that have been explored to a limited degree in such models. The aim here is to provide a robust tool, based on a commercial computational platform, that will allow regulators and other concerned parties access to modeling results, permitting more effective guiding of site investigation and remediation efforts. This portion of the program will involve close collaboration with our state agency partners, in providing access to new detailed site characterization information necessary for model validation. At the same time, we will continue an experimental examination of many of the factors that play an important role in determining vapor concentrations in mixed environments. The influence of different parts of the actual soil matrix will also be examined for such systems (e.g., black carbons, humic acids, moisture, other free-phase NAPLs). Specific Aims of this project: 1. To obtain new experimental data on SVOC mixtures of relevance in vapor exposure scenarios. 2. To continue to develop a robust 3-dimensional model of the vapor intrusion phenomenon, including transient effects, complicated geologies, biodegradation and partitioning. 3. Experimentally explore the partitioning of vapors in the subsurface on black carbon, soil, moisture, NAPL/NAPS as an input to the model in 2 above. 4. Work with state partners to validate the modeling approach with real field data, and make the model available to them as a regulatory tool.